ArcelorMittal Tailored Blanks (AMTB) produces laser welded blanks for cars. AMTB uses data to maintain the quality of the production lines. With a diverse landscape of technologies and production lines, it is challenging to gather relevant insights from the data of AMTB’s machines and inspection systems. Interested to find out how Dimensys and ArcelorMittal gather the necessary data?
Gathering production data
Industry standards such as OPC-servers and historians are used to obtain data from the production process. The OPC-server connects to the machine and saves data including time format in the historian. A historian can be compared to an airplane’s flight recorder.
''This ensures that production and quality personnel interprets the data correctly.''
''In the past, we strived to save all process- and qualitative data in a central data warehouse. With all AMTB and Dimensys’ combined experience, it was decided to shift the focus and make all the data available through portals. This ensures that production and quality personnel interprets the data correctly'', says Nik Vandenweyer, Managing Director bij Dimensys Technical Consultants.
Curious which production data is collected? Or what plans AMTB has for the future? Then watch the video:
Portals for production personnel
The portals give direct insight into relevant data to production personnel and the possibility to zoom into details.
Maarten Depamelaere, CIO at ArcelorMittal Tailored Blanks, explains: ''Think about welding power during the welding process, the coils of steel out of which a steel sheet is produced and the results from the inspection system.''
''AMTB is planning to apply Machine Learning to predict production stages.''
''We have chosen for a combination of technologies to make the integration between the inspection system and the interface as efficient as possible. This methodology is suitable to apply to multi AMTB-production sites in Europe, which also enables them to keep the IT costs low. In addition, the portals are designed to be flexible which allows for the addition of new inspection systems or process parameters with relatively little IT work.'', says Vandenweyer.
Prediction with Machine LearningDepamelaere explains that technological development offers new chances for production companies: ''AMTB is planning to apply Machine Learning to predict production stages. This enables us to make early adjustments which increases the effectiveness of the production process even further.''
''Another opportunity is the price drop for industrial sensors. Nowadays, we still use a lot of machines that not connected to process control systems. The addition of industrial sensors allows organizations to measure these processes as well. Thus, more and more data can be gathered and adapted to make the processes more efficient.'', he continues.
Tip! Read also these articles:
- Optimizing production processes at Brüggen GmbH
- Microsoft recognizes Dimensys as a Gold Partner
- Optimizing zinc by more effective use of sensor data
- [Dutch] ArcelorMittal en Dimensys delen toekomstbeeld 'Smart Industries' op RTL7
Would you like to know more? Download the story of Brüggen about their experiences with integrated production control/MES.